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Halley -> SimpleHalley
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src/SimpleNonlinearSolve.jl

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@@ -88,8 +88,7 @@ PrecompileTools.@compile_workload begin
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end
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end
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# DiffEq styled algorithms
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export Bisection, Brent, Broyden, LBroyden, SimpleDFSane, Falsi, Halley, Klement,
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export Bisection, Brent, Broyden, LBroyden, SimpleDFSane, Falsi, SimpleHalley, Klement,
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Ridder, SimpleNewtonRaphson, SimpleTrustRegion, Alefeld, ITP
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export BatchedBroyden, BatchedSimpleNewtonRaphson, BatchedSimpleDFSane
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src/halley.jl

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@@ -1,6 +1,6 @@
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"""
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```julia
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Halley(; chunk_size = Val{0}(), autodiff = Val{true}(),
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SimpleHalley(; chunk_size = Val{0}(), autodiff = Val{true}(),
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diff_type = Val{:forward})
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```
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@@ -28,16 +28,16 @@ and static array problems.
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`Val{:forward}` for forward finite differences. For more details on the choices, see the
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[FiniteDiff.jl](https://github.com/JuliaDiff/FiniteDiff.jl) documentation.
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"""
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struct Halley{CS, AD, FDT} <: AbstractNewtonAlgorithm{CS, AD, FDT}
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function Halley(; chunk_size = Val{0}(), autodiff = Val{true}(),
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struct SimpleHalley{CS, AD, FDT} <: AbstractNewtonAlgorithm{CS, AD, FDT}
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function SimpleHalley(; chunk_size = Val{0}(), autodiff = Val{true}(),
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diff_type = Val{:forward})
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new{SciMLBase._unwrap_val(chunk_size), SciMLBase._unwrap_val(autodiff),
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SciMLBase._unwrap_val(diff_type)}()
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end
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end
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function SciMLBase.__solve(prob::NonlinearProblem,
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alg::Halley, args...; abstol = nothing,
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alg::SimpleHalley, args...; abstol = nothing,
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reltol = nothing,
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maxiters = 1000, kwargs...)
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f = Base.Fix2(prob.f, prob.p)

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